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Line spectral pairs

Line spectral pairs (LSP) or line spectral frequencies (LSF) are used to represent linear prediction coefficients (LPC) for transmission over a channel.[1] LSPs have several properties (e.g. smaller sensitivity to quantization noise) that make them superior to direct quantization of LPCs. For this reason, LSPs are very useful in speech coding.

LSP representation was developed by Fumitada Itakura,[2] at Nippon Telegraph and Telephone (NTT) in 1975.[3] From 1975 to 1981, he studied problems in speech analysis and synthesis based on the LSP method.[4] In 1980, his team developed an LSP-based speech synthesizer chip. LSP is an important technology for speech synthesis and coding, and in the 1990s was adopted by almost all international speech coding standards as an essential component, contributing to the enhancement of digital speech communication over mobile channels and the internet worldwide.[3] LSPs are used in the code-excited linear prediction (CELP) algorithm, developed by Bishnu S. Atal and Manfred R. Schroeder in 1985.

Mathematical foundation edit

The LP polynomial   can be expressed as  , where:

  •  
  •  

By construction, P is a palindromic polynomial and Q an antipalindromic polynomial; physically P(z) corresponds to the vocal tract with the glottis closed and Q(z) with the glottis open.[5] It can be shown that:

  • The roots of P and Q lie on the unit circle in the complex plane.
  • The roots of P alternate with those of Q as we travel around the circle.
  • As the coefficients of P and Q are real, the roots occur in conjugate pairs

The Line Spectral Pair representation of the LP polynomial consists simply of the location of the roots of P and Q (i.e.   such that  ). As they occur in pairs, only half of the actual roots (conventionally between 0 and  ) need be transmitted. The total number of coefficients for both P and Q is therefore equal to p, the number of original LP coefficients (not counting  ).

A common algorithm for finding these[6] is to evaluate the polynomial at a sequence of closely spaced points around the unit circle, observing when the result changes sign; when it does a root must lie between the points tested. Because the roots of P are interspersed with those of Q a single pass is sufficient to find the roots of both polynomials.

To convert back to LPCs, we need to evaluate   by "clocking" an impulse through it N times (order of the filter), yielding the original filter, A(z).

Properties edit

Line spectral pairs have several interesting and useful properties. When the roots of P(z) and Q(z) are interleaved, stability of the filter is ensured if and only if the roots are monotonically increasing. Moreover, the closer two roots are, the more resonant the filter is at the corresponding frequency. Because LSPs are not overly sensitive to quantization noise and stability is easily ensured, LSP are widely used for quantizing LPC filters. Line spectral frequencies can be interpolated.

See also edit

Sources edit

  • Speex manual and source code (lsp.c)
  • "The Computation of Line Spectral Frequencies Using Chebyshev Polynomials"/ P. Kabal and R. P. Ramachandran. IEEE Trans. Acoustics, Speech, Signal Processing, vol. 34, no. 6, pp. 1419–1426, Dec. 1986.

Includes an overview in relation to LPC.

  • "Line Spectral Pairs" chapter as an online excerpt (pdf) / "Digital Signal Processing - A Computer Science Perspective" (ISBN 0-471-29546-9) Jonathan Stein.

References edit

  1. ^ Sahidullah, Md.; Chakroborty, Sandipan; Saha, Goutam (Jan 2010). "On the use of perceptual Line Spectral pairs Frequencies and higher-order residual moments for Speaker Identification". International Journal of Biometrics. 2 (4): 358–378. doi:10.1504/ijbm.2010.035450.
  2. ^ Zheng, F.; Song, Z.; Li, L.; Yu, W. (1998). "The Distance Measure for Line Spectrum Pairs Applied to Speech Recognition" (PDF). Proceedings of the 5th International Conference on Spoken Language Processing (ICSLP'98) (3): 1123–6.
  3. ^ a b "List of IEEE Milestones". IEEE. Retrieved 15 July 2019.
  4. ^ "Fumitada Itakura Oral History". IEEE Global History Network. 20 May 2009. Retrieved 2009-07-21.
  5. ^ http://svr-www.eng.cam.ac.uk/~ajr/SpeechAnalysis/node51.html#SECTION000713000000000000000 Tony Robinson: Speech Analysis
  6. ^ e.g. lsf.c in http://www.ietf.org/rfc/rfc3951.txt

line, spectral, pairs, line, spectral, frequencies, used, represent, linear, prediction, coefficients, transmission, over, channel, lsps, have, several, properties, smaller, sensitivity, quantization, noise, that, make, them, superior, direct, quantization, lp. Line spectral pairs LSP or line spectral frequencies LSF are used to represent linear prediction coefficients LPC for transmission over a channel 1 LSPs have several properties e g smaller sensitivity to quantization noise that make them superior to direct quantization of LPCs For this reason LSPs are very useful in speech coding LSP representation was developed by Fumitada Itakura 2 at Nippon Telegraph and Telephone NTT in 1975 3 From 1975 to 1981 he studied problems in speech analysis and synthesis based on the LSP method 4 In 1980 his team developed an LSP based speech synthesizer chip LSP is an important technology for speech synthesis and coding and in the 1990s was adopted by almost all international speech coding standards as an essential component contributing to the enhancement of digital speech communication over mobile channels and the internet worldwide 3 LSPs are used in the code excited linear prediction CELP algorithm developed by Bishnu S Atal and Manfred R Schroeder in 1985 Contents 1 Mathematical foundation 2 Properties 3 See also 4 Sources 5 ReferencesMathematical foundation editThe LP polynomial A z 1 k 1 p a k z k displaystyle A z 1 sum k 1 p a k z k nbsp can be expressed as A z 0 5 P z Q z displaystyle A z 0 5 P z Q z nbsp where P z A z z p 1 A z 1 displaystyle P z A z z p 1 A z 1 nbsp Q z A z z p 1 A z 1 displaystyle Q z A z z p 1 A z 1 nbsp By construction P is a palindromic polynomial and Q an antipalindromic polynomial physically P z corresponds to the vocal tract with the glottis closed and Q z with the glottis open 5 It can be shown that The roots of P and Q lie on the unit circle in the complex plane The roots of P alternate with those of Q as we travel around the circle As the coefficients of P and Q are real the roots occur in conjugate pairsThe Line Spectral Pair representation of the LP polynomial consists simply of the location of the roots of P and Q i e w displaystyle omega nbsp such that z e i w P z 0 displaystyle z e i omega P z 0 nbsp As they occur in pairs only half of the actual roots conventionally between 0 and p displaystyle pi nbsp need be transmitted The total number of coefficients for both P and Q is therefore equal to p the number of original LP coefficients not counting a 0 1 displaystyle a 0 1 nbsp A common algorithm for finding these 6 is to evaluate the polynomial at a sequence of closely spaced points around the unit circle observing when the result changes sign when it does a root must lie between the points tested Because the roots of P are interspersed with those of Q a single pass is sufficient to find the roots of both polynomials To convert back to LPCs we need to evaluate A z 0 5 P z Q z displaystyle A z 0 5 P z Q z nbsp by clocking an impulse through it N times order of the filter yielding the original filter A z Properties editLine spectral pairs have several interesting and useful properties When the roots of P z and Q z are interleaved stability of the filter is ensured if and only if the roots are monotonically increasing Moreover the closer two roots are the more resonant the filter is at the corresponding frequency Because LSPs are not overly sensitive to quantization noise and stability is easily ensured LSP are widely used for quantizing LPC filters Line spectral frequencies can be interpolated See also editLog area ratiosSources editSpeex manual and source code lsp c The Computation of Line Spectral Frequencies Using Chebyshev Polynomials P Kabal and R P Ramachandran IEEE Trans Acoustics Speech Signal Processing vol 34 no 6 pp 1419 1426 Dec 1986 Includes an overview in relation to LPC Line Spectral Pairs chapter as an online excerpt pdf Digital Signal Processing A Computer Science Perspective ISBN 0 471 29546 9 Jonathan Stein References edit Sahidullah Md Chakroborty Sandipan Saha Goutam Jan 2010 On the use of perceptual Line Spectral pairs Frequencies and higher order residual moments for Speaker Identification International Journal of Biometrics 2 4 358 378 doi 10 1504 ijbm 2010 035450 Zheng F Song Z Li L Yu W 1998 The Distance Measure for Line Spectrum Pairs Applied to Speech Recognition PDF Proceedings of the 5th International Conference on Spoken Language Processing ICSLP 98 3 1123 6 a b List of IEEE Milestones IEEE Retrieved 15 July 2019 Fumitada Itakura Oral History IEEE Global History Network 20 May 2009 Retrieved 2009 07 21 http svr www eng cam ac uk ajr SpeechAnalysis node51 html SECTION000713000000000000000 Tony Robinson Speech Analysis e g lsf c in http www ietf org rfc rfc3951 txt Retrieved from https en wikipedia org w index php title Line spectral pairs amp oldid 1134937799, wikipedia, wiki, book, books, library,

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